An extended set of yeast-based functional assays accurately identifies human disease mutations

Abstract

We can now routinely identify coding variants within individual human genomes. A pressing challenge is to determine which variants disrupt the function of disease-associated genes. Both experimental and computational methods exist to predict pathogenicity of human genetic variation. However, a systematic performance comparison between them has been lacking. Therefore, we developed and exploited a panel of 26 yeast-based functional complementation assays to measure the impact of 179 variants (101 disease-and 78 non-disease-associated variants) from 22 human disease genes. Using the resulting reference standard, we show that experimental functional assays in a 1-billion-year diverged model organism can identify pathogenic alleles with significantly higher precision and specificity than current computational methods.

A framework for exhaustively mapping functional missense variants

“…Although each is an imperfect measure of the functionality of amino acid changes (Sun et al , 2016), each should and did correlate with DMS results (Fig 1D top panel, Appendix Fig S1). Finally, we confirmed that, as expected, amino acid residues on the protein surface are more tolerant to mutation than those in the protein core or within interaction interfaces (Fig 1D, bottom panel).…”

“…For Stage 3—selection for clones encoding a functional protein—we employed a S. cerevisiae functional complementation assay (Jiang & Koltin, 1996; Sun et al , 2016), based on human UBE2I 's ability to rescue growth at an otherwise‐lethal temperature in a yeast strain carrying a temperature‐sensitive (ts) allele of the UBE2I ortholog UBC9 . Despite a billion years of divergence, yeast functional complementation assays can accurately discriminate pathogenic from non‐pathogenic human variants (Sun et al , 2016).…”

“…Despite a billion years of divergence, yeast functional complementation assays can accurately discriminate pathogenic from non‐pathogenic human variants (Sun et al , 2016). The plasmid library from Stage 3 was transformed en masse into the appropriate ts strain.…”

“…For example, gene panel sequencing aimed at identifying germline cancer risk variants in families yielded VUS for the majority of missense variants (Maxwell et al , 2016). Functional variants can be predicted, but when high precision is required, computational tools (Adzhubei et al , 2010; Choi et al , 2012) detect only one‐third as many pathogenic variants as experimental assays (Sun et al , 2016). Unfortunately, validated experimental assays enabling rapid clinical interpretation of variants are not available for the vast majority of human disease genes.…”

“…Functional complementation assays test the variant gene's ability to rescue the phenotype caused by reduced activity of the wild‐type gene (or its ortholog in the case of trans‐species complementation) (Lee & Nurse, 1987; Osborn & Miller, 2007). Cell‐based functional complementation assays can accurately identify disease variants across a diverse set of human disease genes (Sun et al , 2016). …”